With the proliferation of viewing platforms, file formats and streaming technologies competing in today's online media ecosystem, today's networks are more congested with video than ever. This is mainly due to two factors: the quality expectations of consumers, which drives resolution and bitrates higher, and the sheer amount of video that crosses the network, driven by the shift to Over The Top (OTT) streaming of video, and video consumption in mobile devices.
Video encoding has been widely deployed in many applications and equipment, ranging from digital cinema, mobile handsets, cable and satellite digital video transmissions, to machine vision and recognition systems, etc. To counter the trend of network congestion, the goal of video encoding is often to create an encoded video which has maximal quality and best user experience, while making an effort to reduce video bitrates, given a set of limited resources such as total bandwidth, computation power etc. Some of the currently available video encoders may focus on encoding at a certain bit-rate without considering the encoded video quality, whereas some others may target at achieving a given quality criterion while neglecting time and bit consumption of such encoding. It is widely acknowledged that optimal encoding and re-encoding of video content, such as, e.g., video compression and recompression, to provide an optimal video encoding solution that is both efficient and cost-effective remains as a longstanding challenge in the field.